Seminar Software Methods & Technologies for Virtual Aircraft

Description

In this seminar, students will analyze and discuss scientific publications on a topic in the field of aerospace engineering. Students will learn to independently elaborate the content of the publications and comprehensively present the result of their literature study.

Teacher

Prof. Dr. Sabine Roller

Format

2 SWS seminar, self-study
2.5 credits

Examination

Oral presentation (30min, 20mins talk + 10mins Q&A)

Grade Scale

We'll use the guideline from here.

Creditability

CMS-SEM, INF-D-940, INF-VERT1. INF-VERT2, INF-VERT3, INF-PM-FOR

Schedule/Registration

Kick off meeting: May 5th, 1.30pm, Melli-Beese room at DLR-SP

Presentations: June 26th, 11.30am - 17.00pm, Melli-Beese room at DLR-SP

Suggested Seminar Papers

• Rohit Zambre, Aparna Chandramowlishwaran: "Lessons Learned on MPI+Threads Communication", https://doi.org/10.48550/arXiv.2206.14285
• Paul Mullowney, Ruipeng Li, Stephen Thomas, Shreyas Ananthan, Ashesh Sharma, Jon Rood, Alan B. Williams, Michael Sprague: "Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations", https://dl.acm.org/doi/10.1145/3458817.3476185
• Kumar Saurabh, Masado Ishii, Milinda Fernando, Boshun Gao, Kendrick Tan, Ming-Chen Hsu, Adarsh Krishnamurthy, Hari Sundar, Baskar Ganapathysubramanian: "Scalable Adaptive PDE Solvers in Arbitrary Domains", https://dl.acm.org/doi/10.1145/3458817.3476220
• Martin Kronbichler, Niklas Fehn, Peter Munch, Maximilian Bergbauer, Karl-Robert Wichmann, Carolin Geitner, Momme Allalen, Martin Schulz, Wolfgang A. Wall: "A Next-Generation Discontinuous Galerkin Fluid Dynamics Solver with Application to High-Resolution Lung Airflow Simulations", https://dl.acm.org/doi/10.1145/3458817.3476171
• Sayan Ghosh, Nathan Tallent, Marco Minutoli, Mahantesh Halappanavar, Ramesh Peri, Ananth Kalyanaraman: "Single-Node Partitioned-Memory for Huge Graph Analytics: Cost and Performance Trade-Offs", https://dl.acm.org/doi/10.1145/3458817.3476156
• Ricardo Vinuesa, Steven L. Brunton: "The Potential of Machine Learning to Enhance Computational Fluid Dynamics", http://arxiv.org/pdf/2110.02085v1
• Charles R. Qi and All: 'PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation', https://arxiv.org/abs/1612.00593
• Satoshi Matsuoka, Jens Domke, Mohamed Wahib, Aleksandr Drozd, Torsten Hoefler: "Myths and Legends in High-Performance Computing", https://arxiv.org/pdf/2301.02432
• Robert Schenck, Ola Rønning, Troels Henriksen and Cosmin E. Oancea: "AD for an Array Language with Nested Parallelism", https://arxiv.org/pdf/2202.10297.pdf
• Hong Zhang , Emil Constantinescu: "Revolve-Based Adjoint Checkpointing for Multistage Time Integration", https://link.springer.com/chapter/10.1007/978-3-030-77961-0_37
• William Moses, Sri Hari Krishna Narayanan, Ludger Paehler, Valentin Churavy, Michel Schanen, Jan Hueckelheim, Johannes Doerfert, Paul Hovland: "Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation", https://c.wsmoses.com/papers/enzymePar.pdf
• Michael Lubasch, Jaewoo Joo, Pierre Moinier, Martin Kiffner, Dieter Jaksch, "Variational quantum algorithms for nonlinear problems", 2020, https://arxiv.org/abs/1907.09032

Prof. Dr. Sabine Roller
Institutsleitung
Institut für Softwaremethoden zur Produkt-Virtualisierung
Dresden
Tel.: +49 351 210718 0